What this category of data looks like
The data for this category is primarily sourced from the low-income population dynamic monitoring platform, resident family economic status verification system, and cross-departmental shared data from public security, human resources and social security, medical insurance, housing and urban-rural development, and tax authorities. The update frequency is once per month. Daily business documents include minimum living allowance application forms, family economic status verification reports, household survey forms, democratic appraisal records, public notice materials, and assistance approval forms. The core fields of these documents focus on family income and property, member relationships, and assistance eligibility. There is no unified fixed format template, and content must be filled in accordance with the requirements of each processing link.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Decentralized cross-departmental shared data sources require multi-turn dialogue to gradually guide users to supplement scattered verification information, avoiding asking for too much content at once and causing resistance. The monthly update frequency means dialogue must support eligibility verification based on the latest monthly data, and monthly data snapshots must be included in the context window. Diverse business document types require prompts to adapt to field extraction logic for different materials, distinguishing information capture rules for scenarios such as application forms and verification reports. Family income and property, as well as member relationships, are core verification fields. Multi-turn dialogue must confirm these fields step-by-step in accordance with the verification process, avoiding missing key verification items.
How to set up the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique work order ID of the assistance application | Ensure multi-turn dialogue context is bound to the corresponding business application, avoiding context confusion between different applications |
messages | Retain the last 10 rounds of dialogue content | Adapt to the step-by-step inquiry processing rhythm of civil affairs business, control context load |
variables | Preload cross-departmental shared data snapshots updated monthly | Ensure dialogue verification is based on the latest monthly data, aligning with data update frequency requirements |
| Maximum context length | 8000–12000 characters | Accommodate field content from multiple business documents and complete dialogue history |
| Prompt optimization | Configure by business process link | Adapt to field extraction logic for different documents such as minimum living allowance application forms and verification reports |
Three common misconfigurations
- Issue: Subsequent rounds of multi-turn dialogue cannot call the family income verification results generated in the previous round as input, leading to repeated inquiries or missing verification items. Cause:
chatIdis not correctly bound, or themessagescontent from the previous round is not fully passed into the current dialogue context. - Issue: Clicking a business document link in streaming output only overwrites the current page, and cannot jump to a new page. Cause: Interactive rules for streaming output are not configured, only plain text links are returned, and no jumpable interactive identifiers are added.
- Issue: Dialogue requests return a timeout, with status code 504, and cannot obtain verification results from cross-departmental shared data. Cause: The delay characteristic of cross-departmental data queries is not considered, and a reasonable request waiting duration is not set.
How to confirm the configuration is correct
- Initiate a simulated assistance application dialogue, check whether the dialogue context updates synchronously with the bound work order ID.
- Call the API to initiate a multi-turn dialogue, verify whether the output content from the previous round is correctly included in the context parameters of the current round.
- Trigger streaming output, click the returned link, and confirm that the jump behavior meets expectations.
- Simulate a cross-departmental data query scenario, check whether the dialogue can complete verification based on the preloaded monthly data snapshot.
The values provided here are common starting points, and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.